DWT and BPNN Based Fault Detection, Classification and Estimation of Location of HVAC Transmission Line

被引：0
|
作者：
Saha, Binoy [1 ]
Patel, Bikash [1 ]
Bera, Parthasarathi [1 ]
机构：
[1] Kalyani Govt Engn Coll, Dept Elect Engn, Nadia, W Bengal, India
来源：
2016 INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL POWER AND INSTRUMENTATION (ICICPI) | 2016年
关键词：
Discrete Wavelet Ttransform (DWT); Multi-resolution Analysis (MRA); Back Propagation Neural Network(BPNN); Power System Faults; WAVELET TRANSFORM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper presents a technique for detection classification and diagnosis of fault location on overhead transmission lines for different types of fault. Discrete wavelet transform (DWT) has been used for extraction of features of signals of current under faulted condition and back propagation neural network (BPNN) have been used for training the features of current signal for different fault location. It has been found that the coefficients of discrete wavelet transform of fault signal and BPNN satisfactorily detect, classify and locate the fault location.
引用
收藏
页码：174 / 178
页数：5
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